What problem does it solve? Deciding whether a pricing change should ship requires quantifying trade-offs between revenue lift, churn risk, and conversion impact, which teams often estimate with gut feel instead of structured math. ## Core Features & Use Cases - Pricing Impact Modeling: Quantifies ARPU lift, churn-driven revenue loss, conversion changes, and net MRR impact for a proposed pricing change. - Adaptive Questioning: Walks through up to 4 adaptive questions covering change type (price increase, new tier, add-on, usage-based, discount, packaging), expected impact, and current baseline metrics. - Go/No-Go Recommendations: Delivers one of four recommendation patterns (implement broadly, A/B test first, modify approach, or don't change) with sensitivity analysis. - Use Case: A SaaS team considering a 20% price increase for new customers provides current ARPU, churn, and conversion rates, then receives a modeled net revenue impact with grandfathering guidance and monitoring criteria. ## Quick Start Ask the assistant to evaluate whether raising prices 15% for new customers next quarter makes financial sense given your current ARPU, churn rate, and conversion rate.
